The flattened COVID-19 curve in South Korea - and comparative perspectives among high-resource settings

(Last updated on 2020-04-29)

We have learned how South Korea has implemented a trace-test-isolate strategy - universally across the country and consistently from the outset of the epidemic. So, how does the flattened curve in South Korea look like today, and how does it compare to other countries?

We will compare metrics of the epidemic curve in South Korea and other high-resource settings, specifically the Organisation for Economic Co-operation and Development (OECD) member countries. In addition, Taiwan and Singapore are included, considering their exemplary handling of the epidemic (at least until recently). Understanding different epidemic curves to date will help us not only address the current crisis but also prevent, delay, and flatten the next waves.

Hover over each figure to see values and more options.

See data sources and methods at the end.

1. Latest snapshot by country

Before we check the epidemic curve to date, let’s briefly compare cumulative incidence (number of confirmed cases per 100,000 population) and mortality rates. In South Korea (blue bars below), incidence rate is relatively low (left panel), despite widespread testing. Considering different testing rates, COVID-19 specific mortality rate per population (right panel) may be more appropriate to compare across countries. Singapore, South Korea, and Taiwan all have substantially low COVID specific mortality rates. For data values and interactive options, see this.

And, in case you wonder about case fatality rate. South Korea might have relatively less clinically severe patient population, with relatively young patient population.

2. Epidemic curve by country

The epidemic curve in this analysis was constructed based on the number of new confirmed cases each day. Considering vastly different population sizes, the number of new confirmed cases each day per 100,000 population was used, instead of the absolute number. In addition, 7-day rolling averages were used to avoid any isolated peaks/drops, which can be caused by various reasons other than the true course of the epidemic itself (e.g., changes in definition, and lab process delay). Despite varying testing rates, especially at the outset, the shape of the curve provides insight about the epidemic in each country. See annex for further information about methods.

Let’s focus on the first wave of the epidemic, which we define to start when cumulative incidence exceeds 1 confirmed case per 100,000 population. The peak is when the number of new confirmed cases is at its maximum. There are three distinctive phases:

  • Pre-peak phase (red shade in the below figure): Period when the number of new confirmed cases increases. In many countries, though not all, we have seen an exponential growth in the total confirmed cases during this phase.
  • Post-peak phase (orange shade): Period when the number of new confirmed cases declines to the level/threshold where the first wave started.
  • Relative stable phase (yellow shade): The number of new confirmed cases remain more or less stable - under the level before the first wave. Incidence still increases, but at a much slower rate than before. This last phase provides critical opportunities to realign resources in order to prevent, delay, and flatten the next wave.

With successful control of the epidemic, we will see both narrow (in length) and short (in height) peak.

2.1 Flattened curve in South Korea

The data clearly show the three phases in South Korea. The cumulative incidence rate (gray bars, left axis) exceeded 1 per 100,000 population on 2020-02-23, and the daily new cases (black line, right axis) increased steeply, reaching the peak of 1.2 new confirmed cases per 100,000 population on 2020-03-01. Then, new cases started to drop consistently, entering to the second phase (orange shade). Note that the cumulative incidence still increases substantially during the second phase. For over a month, the country has been well into the relatively stable phase (yellow shade) since 2020-03-11. Cumulative incidence has increased at a much lower rate recently.

2.2 OECD countries also in the relative stable phase

Among OECD members, 6 other countries also have entered the relatively stable phase, although the first wave started later. Holding beginning of the first wave on day 0, the following figure presents the length and height of the peak. Except in Greece, the peak height is taller - slightly (Austria, Lithuania, New Zealand, and Slovenia) or substantially (Iceland), and the length of pre and post peak phases is longer. It took longer to enter the stable phase, after the peak. Iceland is the first country that entered the relatively stable phase, among those with a very high peak (see the following section), but it took 52 days to pass the peak phases. Even among these countries, it is important to keep the number of new infections low without any rebound.

2.3 OECD countries not yet in the relative stable phase

Meanwhile, a majority of countries have not yet entered the relatively stable phase. Most of these countries have a substantially higher peak, compared to the above countries.

A few patterns emerge.

  • Some would reach the stable phase soon if the current pace continues (e.g., Austria, Luxembourg, and Switzerland).
  • Some have had rebounds. After a tentative peak, the number of new infections decreased substantially, but then increased again. See Finland and Lithuania below.
  • Some reached or passed the peak only recently. After the peak, new cases decreased immediately and consistently in some countries (e.g., Germany and Italy), while some countries have a wide peak (e.g., Belgium and United States below).
  • Some have entered the first wave, and the curve is going up slowly (e.g., Japan and Mexico). The level is low, but there is no clear sign of decrease.

All countries are presented below in groups, due to varying range of peak height. Top panel has countries with relatively lower peak, and the bottom panel shows countries with higher peak.

2.4 Taiwan, Singapore, and South Korea

Now, back to the three which have been spotlighted for their exemplary handling of the epidemic. Taiwan has shown the best results of epidemic control - with very slow or no apparent progression to the first wave. In Singapore, the first wave started around the same time with South Korea. The outbreak had been controlled successfully for over a month, but recently the number of new cases has increased exponentially. The Singapore case shows the challenges to control the epidemic even under strong public health systems.

3. Putting it all together - timeline, length and height of the peak

To summarize, the first figure below shows the timeline of the first wave and its phases among OECD countries. South Korea had the first wave earlier than any other countries (red dots). It also has one of the shortest length of the peak (between red and yellow dots). Again, the peak length is still to be determined in many countries (with no yellow dot below).

The next figure shows the height of the peak (the maximum number of new confirmed cases per 100,000 population) by country. The peak was relatively low in South Korea, following several other countries.

Finally, if we put together the height of the peak (on a log scale, Y axis) and time to the peak (distance between the red and orange dots above), a positive correlation appears (i.e., the longer the time to peak, the higher the peak).

In summary, data confirm that South Korea is one of several high-resource countries that successfully controlled the first wave of COVID-19 and have moved into the relatively stable final phase of the first wave. A majority of OECD countries have approached or passed the peak, when the number of new cases starts to decrease, though significant rebounds have occurred in some places.

Moving into the more stable phase, in South Korea and all other countries, public heath authorities need to take full advantage of opportunities to realign resources in order to prevent, delay, and flatten the next wave.


METHODS

Data
1. All COVID-19 data (i.e., cumulative confirmed cases and deaths by day) come from JHU/CSSE. Accessed on 2020-04-29.
2. All data on country population come from UN World Population Prospects 2019 Revision. Accessed on April 18, 2020.

Measures The number of new confirmed cases on each date was calculated based on the difference between cumulative numbers over two consecutive days. Then, a seven-day rolling average was calculated, hereinafter referred to as the smoothed number of new confirmed cases. Then, the smoothed number was divided by the total population in the country: the smoothed number of new confirmed cases per 100,000 population.

  • The first wave was defined to start when the cumulative incidence rate exceeds one per 100,000 population. The smoothed number of new confirmed cases at the start of the first wave varies by country, but it averages around 0.5 per 100,000.
  • The peak date of the wave was the date when the smoothed number of new confirmed cases per 100,000 population was at its height.
  • The date entering the stable phase was when the smoothed number of new confirmed cases per 100,000 population was less than the number on the start date of the wave.

COVID-mortality may be a more comparable indicator to understand the full extent of the epidemic, given considerably different testing strategies and testing rates. However, countries are currently at different stages of the curve, and comparison of mortality data would be possible once most countries are in a similar phase of the epidemic (i.e., well in the the stable phase).


See GitHub for data, code, and more information. For typos, errors, and questions, contact me at www.isquared.global

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